Comparison of Capability for Distinguishing Malignant from Benign Prostatic Areas among 3D CEST Imaging, DWI and Combined Descriptors
Motivation: When compared with DWI, 3D CEST imaging has a potential to play a complementary role for improving management of suspected prostatic cancer patients and improve differentiation capability of malignant from benign prostatic area. Goal(s): The goal was to compare the capability for distinguishing malignant from benign prostatic areas among 3D CEST imaging, DWI and combined both information. Approach: This clinical study examined DWI and 3D CEST imaging. Then, ADC, MTRasym and combined descriptors were compared to their diagnostic performance. Results: Specificity and accuracy of combined discriminators were significantly higher than those of MTRasym (p<0.0001) and ADC (p<0.0001). Impact: 3D CEST imaging is considered at least as valuable as DWI and can improve capability for differentiation of malignant from benign prostatic areas with DWI. 3D CEST imaging may play as complementary role for management of suspected prostatic cancer patients.
Authors
- Masao Yui (ORCID: https://orcid.org/0000-0002-2562-0623)
- Daisuke Takenaka (ORCID: https://orcid.org/0000-0002-9432-7180)
- Takeshi Yoshikawa (ORCID: https://orcid.org/0000-0001-5560-5371)
- Hiroyuki Nagata (ORCID: https://orcid.org/0000-0001-7998-955X)
- Kaori Yamamoto (ORCID: https://orcid.org/0000-0003-0884-3419)
- Yoshiharu Ohno (ORCID: https://orcid.org/0000-0002-4431-1084)
- Masato Ikedo (ORCID: https://orcid.org/0000-0002-2701-1899)
- Takahiro Ueda (ORCID: https://orcid.org/0000-0003-2577-3619)
- Yoshiyuki Ozawa (ORCID: https://orcid.org/0000-0002-8252-1947)
- Masahiko Nomura
- Masanori Ozaki
- Yuichiro Sano
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/2687
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00